In the oil and gas industry, seismic prospecting techniques commonly are used to aid in the search for and evaluation of subterranean hydrocarbon reserves. A seismic prospecting operation consists of three separate stages: data acquisition, data processing, and data interpretation, and success of the operation depends on satisfactory completion of all three stages.
In the data acquisition stage, a seismic source is used to generate an acoustic impulse known as a “seismic wavelet” that propagates into the earth and is at least partially reflected by subsurface seismic reflectors, such as interfaces between underground formations having different acoustic impedances. The reflected signals, known as “seismic reflections”, are detected and recorded by an array of seismic receivers located at or near the surface of the earth, in an overlying body of water, or at known depths in boreholes. The seismic energy recorded by each seismic receiver is known as a “seismic data trace.”
During the data processing stage, the raw seismic data traces recorded in the data acquisition stage are refined and enhanced using a variety of procedures that depend on the nature of the geologic structure being investigated and on the characteristics of the raw data traces themselves. In general, the purpose of the data processing stage is to produce an image of the subsurface from the recorded seismic data for use during the data interpretation stage. The image is developed using theoretical and empirical models of the manner in which the seismic signals are transmitted into the earth, attenuated by subsurface strata, and reflected from geologic structures.
The purpose of the data interpretation stage is to determine information about the subsurface geology of the earth from the processed seismic data. The results of the data interpretation stage may be used to determine the general geologic structure of a subsurface region, or to locate potential hydrocarbon reservoirs, or to guide the development of an already discovered reservoir.
It is common for more than one set of seismic data to be available in a region. This may occur when surveys of the same region have been conducted at various times, for example, when new high-resolution surveys are acquired where older poor-quality surveys already exist or where a series of similar surveys are acquired over the production life an oil field to detect unproduced resource, as in time-lapse seismic. This may also occur when surveys with different technologies overlap, such as streamer and ocean bottom cable, and when different sensors are used to record the same seismic signal in a single survey, as in ocean bottom recordings when both hydrophones and geophones record the same seismic signal. This commonly occurs within a single survey when more than one source-receiver pair acquires reflections from essentially the same subsurface location.
When more than one set of seismic data is available in a region, a seismic image of that region can be formed by merging the information in all available data sets. The quality of this merged image is generally superior to the quality of an image formed by any one of the data sets alone.
A general-purpose optimal technique for merging seismic data sets of various vintages, acquisition technologies, or sensor types has not been previously described in a single publication. However, non-optimal techniques for merging restricted classes of seismic data sets have been described. These techniques can be divided into several types: a) techniques for merging data sets of various vintages; b) techniques for merging data sets from different acquisition technologies; c) techniques for merging data sets from different sensor types; and d) stacking techniques for merging data from source-receiver pairs at different locations. Each class of techniques is described below in greater detail.
Differing Ages. It is common in the seismic exploration industry to acquire new surveys over prospective regions where older, lower-resolution surveys are already available. Surveys of different vintages may differ in the density and geometry of measurement locations. Modern marine surveys typically have receivers positioned in a wide swath behind a survey vessel by means of multiple towed streamers, creating three-dimensional subsurface images. Older surveys often had only a line of receivers in a single streamer behind a survey vessel, creating a two-dimensional “slice” image of the subsurface. Marine surveys may employ different air gun array configurations creating different source wavelets, different hydrophone grouping and spacing within the streamer creating different directional sensitivities, and different streamer towing depths creating different “surface ghost” effects from interference between the direct path and surface reflection. The direction of acquisition may vary, making the distribution of reflection azimuths different at subsurface reflection points. Noise levels may vary between surveys, depending on weather conditions, the presence of other vessels, or even other seismic activity. Newer surveys typically offer improved signal-to-noise ratio in the acquired data due to continuing improvements in source and receiver technology. While a newer survey may afford better image quality than an older one, both surveys contain information. In principle, by merging the surveys a new image can be formed which contains more information than was available in either survey alone.
Rickett and Lumley (2001) published an example of merging data sets of differing age in four-dimensional or time-lapse seismic, where surveys of the same region are taken at intervals of time during the production of hydrocarbons from a field. The subsurface differences observed between these surveys are due to the production of hydrocarbons and indicate which portions of a subsurface reservoir are being drained during production.
Differing Acquisition Technology. The least expensive technique for acquiring marine seismic data is the towed streamer. However it is difficult to safely operate towed streamer surveys in the vicinity of obstacles, like offshore platforms. Streamer surveys will typically divert around obstacles, and it is common practice to fill in the missing coverage near the obstacle with ocean bottom cable surveys which can be safely operated closer to obstacles.
Ikelle in two publications (1999, 2002) combines OBC data with streamer data by convolving the data types with each other. This combined data, which is shown to be an estimate of high-order multiples, is then subtracted from the measured OBC data to achieve multiple attenuation. Verschuur (1999) uses a similar approach where the data itself becomes a filtering operator to accomplish multiple attenuation in OBC data.
Differing Sensor Type. Multiple reflections pose a serious problem in marine seismic data processing. Co-located pressure and velocity measurements made at the ocean bottom can be combined—and are combined in industry practice—to produce seismic records with reduced multiple levels. Various multiple suppression techniques have been proposed in the literature based on combining bottom pressure and velocity measurements. Classifications of these techniques include direct summation, summation followed by filtering, filtering pressure and velocity records separately then summing, muting methods, and data-based surface related multiple attenuation (SRME) methods. In direct summation techniques, the pressure and velocity records are simply added together, possibly with different weightings applied to the two data sets as disclosed in U.S. Pat. No. 4,979,150, Barr (1999), and Bale (1998). In summation followed by filtering, the pressure and velocity records are added together in such a way that the summed data set can then be filtered to remove additional multiple energy. U.K. Patent No. 2,338,302 discloses a summation followed by filtering technique and U.S. Pat. No. 5,835,451, Paffenholz (1998), and Soubaras (1996) disclose techniques involving filtering pressure and velocity records separately, then summing. In muting methods, certain arrivals are identified as dominantly multiple-related by comparing the polarity of pressure and velocity measurements, and then simply muted and are disclosed in U.S. Pat. Nos. 6,678,207 and 5,621,700. Finally, Matson (2002) discloses a data-based surface related multiple attenuation (SRME) methods, where a non-linear process of autoconvolution and subtraction of the data is performed.
Differing Source-Receiver Pairs. Seismic surveys commonly obtain seismic signals from different source—receiver pairs which image essentially the same subsurface location. These signals are commonly combined to enhance the image of the common subsurface location. This combination is accomplished by aligning the reflections from the common subsurface locations in time, an operation called “moveout correction”, and then summing the signals, an operation called “stacking”. (Mayne, 1967) However, such a technique provides the optimal unbiased image of the subsurface location only when the moveout correction does not significantly alter the signal and when the noise in all the signals is uncorrelated, Gaussian, and of equal variance. In (Robinson, 1970), the author analyzed stacking and proposed using a SNR-based weighted stack to further minimize the noise. In addition to reducing random noises, stacking of signals from sensors at different offsets has the benefit of attenuating multiples (Cassano and Rocca, 1973; Schoenberger, 1996). In (Cassano and Rocca, 1973), the authors first filter the signal from each receiver before stacking. In (Schoenberger, 1996), the author proposes a weighted stack, with the weights determined by solving a set of optimization equations.
The filtering and summing operations involved in merging data sets can be performed temporally in time or frequency domain and spatially in offset or wavenumber domain as disclosed in Amundsen (2001), Amundsen and Ikelle (2001), Yan (2001), and Schalkwijk (2001). The use of the term “filtering” in this disclosure will include filtering operations in frequency domain and in frequency/wavenumber domain.
In Lehmann (1999), the term “sufficient statistic” is defined and its significance in estimating a set of parameters from a set of measurements described. A “sufficient statistic” is a new set of (typically fewer) numerical values which are derived from the measurements through mathematical operations and contain all the information about the parameters which was originally in the measurements. Whether a particular transformation of measurements creates a sufficient statistic for the parameters depends on the “measurement model” assumed to relate the measurements to the parameters.
In the prior art, the methods for combining seismic data sets are not designed to form a sufficient statistic for the desired data set. Accordingly, there is a need for a method that optimally merges two or more seismic data sets of the same subsurface region using a sufficient statistic. The present invention satisfies this need.